Handles 500+ concurrent PDF generations without crashing. Pattern 11: PDF Optimization via Object De-duplication PDFs from Microsoft Word contain duplicate fonts and images. Use pypdf 's optimize :
from pypdf import PdfReader reader = PdfReader("doc.pdf") meta = reader.metadata # The hidden gold: print(f"Producer: {meta.get('/Producer')}") # 'Adobe Acrobat' vs 'Chrome PDF' print(f"Page layout: {reader.page_layout}") # SinglePage, TwoColumnLeft Route PDFs based on /Producer to different parsing pipelines (e.g., Chrome-generated PDFs need different table detection). Pattern 10: Asynchronous PDF Generation (FastAPI + ReportLab) The old sync pattern blocks the event loop. Modern reportlab with asyncio.to_thread : Handles 500+ concurrent PDF generations without crashing
In the landscape of enterprise automation, document engineering, and data extraction, two technologies have reached an inflection point: Portable Document Format (PDF) and Python . For over a decade, Python has been the duct tape of the data world; but in the last 12 months (the "modern 12"), it has evolved into a surgical instrument for PDF manipulation. and data extraction
@app.get("/pdf") async def get_pdf(): pdf_bytes = await gen_pdf() return StreamingResponse(io.BytesIO(pdf_bytes), media_type="application/pdf") Chrome-generated PDFs need different table detection).